Director - Drug Discovery AI

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work, but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.

About Lilly

At Lilly, everything we do starts with patients. We unite caring with discovery to make life better for people around the world. Headquartered in Indianapolis, Indiana, our global team of over 50,000 employees work with urgency and purpose to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. We bring our best to this work because people depend on it. If you're driven by purpose and determined to make a meaningful difference for patients, we invite you to bring your skill and your commitment to Lilly.

About Technology@Lilly

At Lilly, technology is not a support function. It is how a global medicine company operates, innovates, and delivers. Lilly in Bengaluru builds the capabilities that make this possible, cloud platforms, AI systems, and automation at enterprise scale, all in service of a purpose that makes this technology work genuinely distinctive, from advancing drug discovery to enabling connected clinical trials to keeping a global medicine company running at the standard patients deserve.

Role Overview

As a Director of Drug Discovery AI, you will set scientific direction and technical strategy for AI research programs that span the full drug discovery value chain. This includes target identification and validation, hit finding, lead optimization, ADMET and developability, and translational biomarker discovery across small molecules, biologics, and genetic medicines.

You will lead a team of AI scientists, AI engineers, and computational chemists and biologists, partnering closely with experimental scientists in Lilly Research Laboratories to turn frontier AI research into scalable, production-grade capabilities that accelerate the delivery of new medicines. AI is your core expertise: you are a world-class machine learning scientist with deep fluency across chemistry, biology, and genomics, and you can see how advances in one modality or discovery stage can be applied to another.

This role requires a track record of scientific leadership, strategic influence, and building large-scale AI research programs in the life sciences. In return, you will have the scale to make your work count: Lilly’s proprietary chemical, biological, and experimental data; the most powerful AI supercomputer owned and operated by a pharmaceutical company; and strategic collaborators.

Key Responsibilities

Advance foundation models and next-generation AI methods

Set the architectural direction for large-scale foundation models trained on Lilly’s proprietary chemical, biological, and experimental data, including multimodal models that integrate molecules, sequences, structures, cellular phenotypes, omics, and assay data.

Advance the methods that most improve discovery outcomes, including self-supervised and multi-task learning, generative and diffusion-based approaches, geometric and physics-informed models, novel model architectures, and agentic AI systems for scientific reasoning and workflow orchestration.

Ensure rigorous evaluation of new methods against leading academic and industry benchmarks and against prospective experimental outcomes

Build and lead people

Build, mentor, and develop high-performing teams of AI scientists, AI engineers, and computational chemists and biologists, and cultivate the next generation of research leaders.

Foster a culture of scientific excellence, open inquiry, and cross-disciplinary collaboration, with a strong commitment to scientific rigor, data integrity, intellectual property protection, and responsible AI.

Deliver measurable impact and external influence

Translate research breakthroughs into quantifiable improvements in discovery outcomes, such as hit rates, cycle times, candidate quality, and probability of technical success.

Represent Lilly in the external scientific community through publications, partnerships, and conference leadership.

Basic Qualifications

PhD in Machine Learning, Computer Science, Computational Chemistry, Computational Biology, Physics, Statistics, or a closely related quantitative field.

6+ years of post-PhD experience in machine learning research in industry or academia, including leading research programs, setting technical strategy, and managing scientific teams.

Proficiency in Python and modern ML frameworks such as PyTorch, with hands-on experience developing and evaluating novel models.

Preferred Qualifications

Breadth across drug discovery domains, such as computational chemistry, molecular design, protein and antibody engineering, genomics and multi-omics, structural biology, cell and imaging phenotyping, and ADMET prediction, with recognized impact in at least one and working fluency across several others.

A record of AI-derived molecules or targets progressing toward the clinic, gained in pharma or biotech or through close partnership with wet-lab teams.

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form ( https://careers.lilly.com/us/en/workplace-accommodation ) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.

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